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New paper proposes unified framework linking dataset aggregation and exact machine unlearning

This story is from 2026-11-06. It is preserved in the archive; the latest stories are on the live feed.

A new arXiv paper studies renormalization, normalized log-linear combination, and nesting of Gibbs probability measures, yielding a unified framework for training-dataset aggregation and exact machine unlearning.

Read the full story at arXiv stat.ML ↗

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  1. 2026-11-06 05:00 · arXiv stat.ML
    A Unified Framework for Training-Dataset Aggregation and Exact Machine Unlearning via Gibbs Probability Measures

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